Journalism and artificial intelligence: some notes

I think that AI and machine learning is a big deal for journalism and news information. Possibly as important as the other developments we have seen in the last 20 years such as online platforms, digital tools and social media. My 2008 book on how journalism was being revolutionised by technology was called SuperMedia because these technologies offered extraordinary opportunities to make journalism much more efficient and effective – but also to transform what we mean by news and how we relate to it as individuals and communities. Of course, that can be super good or super bad.

Artificial intelligence and machine learning can help the news media with its three core problems:

The overabundance of information and sources that leave the public confused

The credibility of journalism in a world of disinformation and falling trust and literacy

The Business model crisis – how can journalism become more efficient – avoiding duplication; be more engaged, add value and be relevant to the individual’s and communities’ need for quality, accurate information and informed, useful debate.

But like any technology they can also be used by bad people or for bad purposes: in journalism that can mean clickbait, misinformation, propaganda, and trolling.

Some caveats about using AI in journalism:

Narratives are difficult to program. Trusted journalists are needed to understand and write meaningful stories.

Artificial Intelligence increases quantity, not quality. It’s still up to the editorial team and developers to decide what kind of journalism the AI will help create.

AI in its broadest sense provides all sorts of opportunities for journalism – and journalism needs all the help it can get right now – not just to boost its core value but to re-form its relationship to the public and its ability to deal with the new information ecosystem. Here are a few applications that I think are interesting:

New platform opportunities such as voice/Alexa/Google assistant – or Augmented Reality – and of course, blockchain

Of course – like any technological change there are going to be negatives as well as positives:

Automated journalism still needs to be edited by humans

Verification at its most important is always humanly complex

Platforms find it difficult to us AI at scale and at speed and in detail (YouTube Crisis Actors) and can be gamed

Marketing – how do we use AI to find new people not just to track a core readership – how do we use it to find underserved communities

Personalisation – how do we use AI to provide diversity not just favourites

Discovery – data sets are often very bad – eg court records in the UK

Blockchain – really interesting work being done on decentralised content creation and dissemination but can you scale it and make it useful in real time and in a news cycle?

Then there are the broader structural issues around this profound shift to a new tech paradigm:

Does mainstream journalism have the skills and insights to make the most of the changes? Are savings ploughed back into ‘real’ human journalism?

Trust and transparency – there are a new set of ethical dilemmas that need to be addressed – with AI how do we know who has created content and the sources? How do we hold them accountable? How do you even know it’s a machine?

Plus the usual algorithmic biases of gender and the dangers of tech companies and developers gaining power at the expense of the journalists or the public. There’s nothing innately democratic or progressive about AI.

“there seems to be no downside to having a deep understanding of owned data. For media companies, data aides decisions around what to cover, to what depth, on which platforms and what time of day or week; it boosts subscriber numbers by understanding behavior and key triggers for conversion; and it helps advertisers target to the degree of understanding when readers and viewers have an intent to buy.”

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